Araştırma Makalesi
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Yıl 2019, Cilt: 23 Sayı: 5, 775 - 781, 01.10.2019

Harun Akkuş

https://doi.org/10.16984/saufenbilder.490668
Cited By: 4

Öz

Kaynakça

  • [1] Z. Hessainia, A. Belbah, M.A. Yallese, T. Mabrouki, J. F. Rigal, “On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations”, Measurement, 46(5), 1671-1681, 2013
  • [2] M. Mia, N.R. Dhar, “Prediction of surface roughness in hard turning under high pressure coolant using artificial neural network”, Measurement, 92, 464-474, 2016
  • [3] Y. Yamane, T. Ryutaro, S. Tadanori, I.M. Ramirez, Y. Keiji, “A new quantitative evaluation for characteristic of surface roughness in turning”, Precision Engineering, 50, 20-26, 2017
  • [4] G.S. Ahmed, S.S. H. Quadri, M. S. Mohiuddin, “Optimization of feed and radial force in turning process by using Taguchi design approach”, Materials Today: Proceedings, 2(4-5), 3277-328, 2015
  • [5] D. Deepak, B. Rajendra, “Optimization of Machining Parameters for Turning of Al6061 using Robust Design Principle to minimize the surface roughness”, Procedia Technology, 24, 372-378, 2016
  • [6] D.M. D’Addona, S.J. Raykar, “Analysis of surface roughness in hard turning using wiper insert geometry”, Procedia CIRP, 41, 841-846, 2016
  • [7] E.G. Plaza, P.N. López, “Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations”, Mechanical Systems and Signal Processing, 98, 902-919, 2018
  • [8] X. Yue, M. Xu, W. Du, C. Chu, “Effect of cutting edge radius on surface roughness in diamond tool turning of transparent MgAl2O4 spinel ceramic”, Optical Materials, 71, 129-135, 2017
  • [9] S. Debnath, M.M. Reddy, Q.S. Yi, “Influence of cutting fluid conditions and cutting parameters on surface roughness and tool wear in turning process using Taguchi method”, Measurement, 78, 111-119, 2016
  • [10] S. Ramesh, L. Karunamoorthy, K. Palanikumar, “Measurement and analysis of surface roughness in turning of aerospace titanium alloy (gr5)”, Measurement, 45(5), 1266-1276, 2012
  • [11] P. Zhang, Z. Liu, “Modeling and prediction for 3D surface topography in finish turning with conventional and wiper inserts”, Measurement, 94, 37-45, 2016
  • [12] İ. Asiltürk, H. Akkuş, “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, 44(9), 1697-1704, 2011
  • [13] Agrawal, S. Goel, W.B. Rashid, M. Price, “Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRc), Applied Soft Computing, 30, 279-286, 2015
  • [14] M. Nalbant, H. Gökkaya, G. Sur, “Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning”, Materials & Design, 28 (4), 1379-1385, 2007
  • [15] İ. Tekaüt, M. Günay, U. Şeker, “Optimization of cutting parameters and chip breaker form by Taguchi method in turning operations”, 6th International Advanced Technologies Symposium, 127-131, 2011
  • [16] Torres, I. Puertas, C.J. Luis, “Surface roughness analysis on the dry turning of an Al-Cu alloy”, Procedia engineering, 132, 537-544, 2015
  • [17] T. Asakura, “Surface roughness measurement”, Speckle metrology, 11-49, 1978
  • [18] M. Tomov, M. Kuzinovski, P. Cichosz, “Modeling and prediction of surface roughness profile in longitudinal turning”, Journal of Manufacturing Processes, 24, 231-255, 2016
  • [19] J. Chen, Q. Zhao, “A model for predicting surface roughness in single-point diamond turning”, Measurement, 69, 20-30, 2015
  • [20] T. Mikołajczyk, K. Nowicki, A. Bustillo, D.Y. Pimenov, “Predicting tool life in turning operations using neural networks and image processing”, Mechanical Systems and Signal Processing, 104, 503-513, 2018
  • [21] G.M.A. Acayaba, P.M. Escalona, “Prediction of surface roughness in low speed turning of AISI316 austenitic stainless steel”, CIRP Journal of Manufacturing Science and Technology, 11, 62-67, 2015
  • [22] J.C. Pereira, R.G. Ruiz, “Influencia de los parámetros de corte y geometría de la herramienta en la rugosidad superficial obtenida en operaciones de torneado del bronce SAE 40”, Revista Ingeniería, 14(3), 77-85, 2007
  • [23] S. Chandraker, “Taguchi analysis on cutting force and surface roughness in turning MDN350 steel”, Materials Today: Proceedings, 2(4-5), 3388-3393, 2015
  • [24] C.L. He, W.J. Zong, Z.M. Cao, T. Sun, “Theoretical and empirical coupled modeling on the surface roughness in diamond turning” Materials & Design, 82, 216-222, 2015

Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel

Yıl 2019, Cilt: 23 Sayı: 5, 775 - 781, 01.10.2019

Harun Akkuş

https://doi.org/10.16984/saufenbilder.490668
Cited By: 4

Öz

In this study, AISI 4140 tempering
steel with 48 HRc hardness was machined on CNC lathe with different cutting
parameters and cooling environment. The Taguchi L9 test design was
developed based on the three-level cutting speed, feed, chip depth and cooling
environment parameters. The average surface roughness (Ra) values were measured
in experiments made according to the L9 test design. Chip form
occurring during turning is photographed. The Signal/Noise (S/N) ratios of the
Taguchi experiment design in the Minitab program have been determined.
According to the experimental results, the most significant effect on the Ra
from the four factors was found in the hand made by the depth of cut. In ANOVA
analysis, it was respectively determined that depth of cut, cutting speed, feed
rate and cooling environment affected 95% confidence in Ra value. It has been
found that the repeat experiments for the optimum parameters yielded about 90%
accuracy compared to the Taguchi estimate.

Anahtar Kelimeler

AISI 4140 turning surface roughness chip formation optimization

Kaynakça

  • [1] Z. Hessainia, A. Belbah, M.A. Yallese, T. Mabrouki, J. F. Rigal, “On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations”, Measurement, 46(5), 1671-1681, 2013
  • [2] M. Mia, N.R. Dhar, “Prediction of surface roughness in hard turning under high pressure coolant using artificial neural network”, Measurement, 92, 464-474, 2016
  • [3] Y. Yamane, T. Ryutaro, S. Tadanori, I.M. Ramirez, Y. Keiji, “A new quantitative evaluation for characteristic of surface roughness in turning”, Precision Engineering, 50, 20-26, 2017
  • [4] G.S. Ahmed, S.S. H. Quadri, M. S. Mohiuddin, “Optimization of feed and radial force in turning process by using Taguchi design approach”, Materials Today: Proceedings, 2(4-5), 3277-328, 2015
  • [5] D. Deepak, B. Rajendra, “Optimization of Machining Parameters for Turning of Al6061 using Robust Design Principle to minimize the surface roughness”, Procedia Technology, 24, 372-378, 2016
  • [6] D.M. D’Addona, S.J. Raykar, “Analysis of surface roughness in hard turning using wiper insert geometry”, Procedia CIRP, 41, 841-846, 2016
  • [7] E.G. Plaza, P.N. López, “Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations”, Mechanical Systems and Signal Processing, 98, 902-919, 2018
  • [8] X. Yue, M. Xu, W. Du, C. Chu, “Effect of cutting edge radius on surface roughness in diamond tool turning of transparent MgAl2O4 spinel ceramic”, Optical Materials, 71, 129-135, 2017
  • [9] S. Debnath, M.M. Reddy, Q.S. Yi, “Influence of cutting fluid conditions and cutting parameters on surface roughness and tool wear in turning process using Taguchi method”, Measurement, 78, 111-119, 2016
  • [10] S. Ramesh, L. Karunamoorthy, K. Palanikumar, “Measurement and analysis of surface roughness in turning of aerospace titanium alloy (gr5)”, Measurement, 45(5), 1266-1276, 2012
  • [11] P. Zhang, Z. Liu, “Modeling and prediction for 3D surface topography in finish turning with conventional and wiper inserts”, Measurement, 94, 37-45, 2016
  • [12] İ. Asiltürk, H. Akkuş, “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, 44(9), 1697-1704, 2011
  • [13] Agrawal, S. Goel, W.B. Rashid, M. Price, “Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRc), Applied Soft Computing, 30, 279-286, 2015
  • [14] M. Nalbant, H. Gökkaya, G. Sur, “Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning”, Materials & Design, 28 (4), 1379-1385, 2007
  • [15] İ. Tekaüt, M. Günay, U. Şeker, “Optimization of cutting parameters and chip breaker form by Taguchi method in turning operations”, 6th International Advanced Technologies Symposium, 127-131, 2011
  • [16] Torres, I. Puertas, C.J. Luis, “Surface roughness analysis on the dry turning of an Al-Cu alloy”, Procedia engineering, 132, 537-544, 2015
  • [17] T. Asakura, “Surface roughness measurement”, Speckle metrology, 11-49, 1978
  • [18] M. Tomov, M. Kuzinovski, P. Cichosz, “Modeling and prediction of surface roughness profile in longitudinal turning”, Journal of Manufacturing Processes, 24, 231-255, 2016
  • [19] J. Chen, Q. Zhao, “A model for predicting surface roughness in single-point diamond turning”, Measurement, 69, 20-30, 2015
  • [20] T. Mikołajczyk, K. Nowicki, A. Bustillo, D.Y. Pimenov, “Predicting tool life in turning operations using neural networks and image processing”, Mechanical Systems and Signal Processing, 104, 503-513, 2018
  • [21] G.M.A. Acayaba, P.M. Escalona, “Prediction of surface roughness in low speed turning of AISI316 austenitic stainless steel”, CIRP Journal of Manufacturing Science and Technology, 11, 62-67, 2015
  • [22] J.C. Pereira, R.G. Ruiz, “Influencia de los parámetros de corte y geometría de la herramienta en la rugosidad superficial obtenida en operaciones de torneado del bronce SAE 40”, Revista Ingeniería, 14(3), 77-85, 2007
  • [23] S. Chandraker, “Taguchi analysis on cutting force and surface roughness in turning MDN350 steel”, Materials Today: Proceedings, 2(4-5), 3388-3393, 2015
  • [24] C.L. He, W.J. Zong, Z.M. Cao, T. Sun, “Theoretical and empirical coupled modeling on the surface roughness in diamond turning” Materials & Design, 82, 216-222, 2015
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Harun Akkuş 0000-0002-9033-309X

Yayımlanma Tarihi 1 Ekim 2019
Gönderilme Tarihi 30 Kasım 2018
Kabul Tarihi 21 Mart 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 23 Sayı: 5

Kaynak Göster

APA Akkuş, H. (2019). Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel. Sakarya University Journal of Science, 23(5), 775-781. https://doi.org/10.16984/saufenbilder.490668
AMA Akkuş H. Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel. SAUJS. Ekim 2019;23(5):775-781. doi:10.16984/saufenbilder.490668
Chicago Akkuş, Harun. “Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel”. Sakarya University Journal of Science 23, sy. 5 (Ekim 2019): 775-81. https://doi.org/10.16984/saufenbilder.490668.
EndNote Akkuş H (01 Ekim 2019) Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel. Sakarya University Journal of Science 23 5 775–781.
IEEE H. Akkuş, “Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel”, SAUJS, c. 23, sy. 5, ss. 775–781, 2019, doi: 10.16984/saufenbilder.490668.
ISNAD Akkuş, Harun. “Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel”. Sakarya University Journal of Science 23/5 (Ekim 2019), 775-781. https://doi.org/10.16984/saufenbilder.490668.
JAMA Akkuş H. Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel. SAUJS. 2019;23:775–781.
MLA Akkuş, Harun. “Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel”. Sakarya University Journal of Science, c. 23, sy. 5, 2019, ss. 775-81, doi:10.16984/saufenbilder.490668.
Vancouver Akkuş H. Experimental and Statistical Investigation of Surface Roughness in Turning of AISI 4140 Steel. SAUJS. 2019;23(5):775-81.

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Analysis of Surface Roughness of Aluminum 5000 Alloys Obtained from Chips After Turning by Taguchi Method
Journal of the Institute of Science and Technology
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CNC Torna Tezgâhlarında Ayna ve Punta Basıncının Yüzey Pürüzlülüğü ve Titreşim Üzerine Etkisinin Taguchi Metodu İle Optimizasyonu
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https://doi.org/10.35193/bseufbd.622853
 Kapak Resmi İndir

Sakarya University Journal of Science (SAUJS)